Mobile Commerce - Analysis and Investigation of the Online Safety, Privacy, and Data Forensics of Amazon and Etsy Apps

The COVID19 pandemic has led to the proliferation of the usage of online shopping applications among millions of customers worldwide. The enormous potential in technological advancements, particularly mobile technology, has directly impacted mobile commerce, where the shopping process has become so convenient. While the benefits of mobile commerce are multi-fold, the current privacy practices and the extent of user data residue in shopping apps have been less explored. In this paper, we have conducted an in-depth, systematic analysis of two of the most popular mobile shopping apps - Amazon and Etsy. Our analysis led to the recovery of user data and shopping activity artifacts from Amazon’s and Etsy’s buyer and seller apps on Android/iOS devices. Based on the user data and artifacts found, we have also discussed the implications of default privacy settings, the importance of online safety policies prior to product listings, and implications for research and practice

Privacy Preserving Internet Browsers: Forensic Analysis of Browzar

With the advance of technology, Criminal Justice agencies are being confronted with an increased need to investigate crimes perpetuated partially or entirely over the Internet. These types of crime are known as cybercrimes. In order to conceal illegal online activity, criminals often use private browsing features or browsers designed to provide total browsing privacy. The use of private browsing is a common challenge faced in for example child exploitation investigations, which usually originate on the Internet. Although private browsing features are not designed specifically for criminal activity, they have become a valuable tool for criminals looking to conceal their online activity. As such, Technological Crime units often focus their forensic analysis on thoroughly examining the web history on a computer. Private browsing features and browsers often require a more in-depth, post mortem analysis. This often requires the use of multiple tools, as well as different forensic approaches to uncover incriminating evidence. This evidence may be required in a court of law, where analysts are often challenged both on their findings and on the tools and approaches used to recover evidence. However, there are very few research on evaluating of private browsing in terms of privacy preserving as well as forensic acquisition and analysis of privacy preserving internet browsers. Therefore in this chapter, we firstly review the private mode of popular internet browsers. Next, we describe the forensic acquisition and analysis of Browzar, a privacy preserving internet browser and compare it with other popular internet browser

Identifying and combating cyber-threats in the field of online banking

This thesis has been carried out in the industrial environment external to the University, as an industrial PhD. The results of this PhD have been tested, validated, and implemented in the production environment of Caixabank and have been used as models for others who have followed the same ideas. The most burning threats against banks throughout the Internet environment are based on software tools developed by criminal groups, applications running on web environment either on the computer of the victim (Malware) or on their mobile device itself through downloading rogue applications (fake app's with Malware APP). Method of the thesis has been used is an approximation of qualitative exploratory research on the problem, the answer to this problem and the use of preventive methods to this problem like used authentication systems. This method is based on samples, events, surveys, laboratory tests, experiments, proof of concept; ultimately actual data that has been able to deduce the thesis proposal, using both laboratory research and grounded theory methods of data pilot experiments conducted in real environments. I've been researching the various aspects related to e-crime following a line of research focusing on intrinsically related topics: - The methods, means and systems of attack: Malware, Malware families of banker Trojans, Malware cases of use, Zeus as case of use. - The fixed platforms, mobile applications and as a means for malware attacks. - forensic methods to analyze the malware and infrastructure attacks. - Continuous improvement of methods of authentication of customers and users as a first line of defense anti- malware. - Using biometrics as innovative factor authentication.The line investigating Malware and attack systems intrinsically is closed related to authentication methods and systems to infect customer (executables, APP's, etc.), because the main purpose of malware is precisely steal data entered in the "logon "authentication system, to operate and thus, fraudulently, steal money from online banking customers. Experiments in the Malware allowed establishing a new method of decryption establishing guidelines to combat its effects describing his fraudulent scheme and operation infection. I propose a general methodology to break the encryption communications malware (keystream), extracting the system used to encrypt such communications and a general approach of the Keystream technique. We show that this methodology can be used to respond to the threat of Zeus and finally provide lessons learned highlighting some general principles of Malware (in general) and in particular proposing Zeus Cronus, an IDS that specifically seeks the Zeus malware, testing it experimentally in a network production and providing an effective skills to combat the Malware are discussed. The thesis is a research interrelated progressive evolution between malware infection systems and authentication methods, reflected in the research work cumulatively, showing an evolution of research output and looking for a progressive improvement of methods authentication and recommendations for prevention and preventing infections, a review of the main app stores for mobile financial services and a proposal to these stores. The most common methods eIDAMS (authentication methods and electronic identification) implemented in Europe and its robustness are analyzed. An analysis of adequacy is presented in terms of efficiency, usability, costs, types of operations and segments including possibilities of use as authentication method with biometrics as innovation.Este trabajo de tesis se ha realizado en el entorno industrial externo a la Universidad como un PhD industrial Los resultados de este PhD han sido testeados, validados, e implementados en el entorno de producción de Caixabank y han sido utilizados como modelos por otras que han seguido las mismas ideas. Las amenazas más candentes contra los bancos en todo el entorno Internet, se basan en herramientas software desarrolladas por los grupos delincuentes, aplicaciones que se ejecutan tanto en entornos web ya sea en el propio ordenador de la víctima (Malware) o en sus dispositivos móviles mediante la descarga de falsas aplicaciones (APP falsa con Malware). Como método se ha utilizado una aproximación de investigación exploratoria cualitativa sobre el problema, la respuesta a este problema y el uso de métodos preventivos a este problema a través de la autenticación. Este método se ha basado en muestras, hechos, encuestas, pruebas de laboratorio, experimentos, pruebas de concepto; en definitiva datos reales de los que se ha podido deducir la tesis propuesta, utilizando tanto investigación de laboratorio como métodos de teoría fundamentada en datos de experimentos pilotos realizados en entornos reales. He estado investigando los diversos aspectos relacionados con e-crime siguiendo una línea de investigación focalizada en temas intrínsecamente relacionadas: - Los métodos, medios y sistemas de ataque: Malware, familias de Malware de troyanos bancarios, casos de usos de Malware, Zeus como caso de uso. - Las plataformas fijas, los móviles y sus aplicaciones como medio para realizar los ataques de Malware. - Métodos forenses para analizar el Malware y su infraestructura de ataque. - Mejora continuada de los métodos de autenticación de los clientes y usuarios como primera barrera de defensa anti- malware. - Uso de la biometría como factor de autenticación innovador. La línea investiga el Malware y sus sistemas de ataque intrínsecamente relacionada con los métodos de autenticación y los sistemas para infectar al cliente (ejecutables, APP's, etc.) porque el objetivo principal del malware es robar precisamente los datos que se introducen en el "logon" del sistema de autenticación para operar de forma fraudulenta y sustraer así el dinero de los clientes de banca electrónica. Los experimentos realizados en el Malware permitieron establecer un método novedoso de descifrado que estableció pautas para combatir sus efectos fraudulentos describiendo su esquema de infección y funcionamiento Propongo una metodología general para romper el cifrado de comunicaciones del malware (keystream) extrayendo el sistema utilizado para cifrar dichas comunicaciones y una generalización de la técnica de Keystream. Se demuestra que esta metodología puede usarse para responder a la amenaza de Zeus y finalmente proveemos lecciones aprendidas resaltando algunos principios generales del Malware (en general) y Zeus en particular proponiendo Cronus, un IDS que persigue específicamente el Malware Zeus, probándolo experimentalmente en una red de producción y se discuten sus habilidades y efectividad. En la tesis hay una evolución investigativa progresiva interrelacionada entre el Malware, sistemas de infección y los métodos de autenticación, que se refleja en los trabajos de investigación de manera acumulativa, mostrando una evolución del output de investigación y buscando una mejora progresiva de los métodos de autenticación y de la prevención y recomendaciones para evitar las infecciones, una revisión de las principales tiendas de Apps para servicios financieros para móviles y una propuesta para estas tiendas. Se analizan los métodos más comunes eIDAMS (Métodos de Autenticación e Identificación electrónica) implementados en Europa y su robustez y presentamos un análisis de adecuación en función de eficiencia, usabilidad, costes, tipos de operación y segmentos incluyendo un análisis de posibilidades con métodos biométricos como innovación.Postprint (published version

Security Protocols and Evidence: Where Many Payment Systems Fail

As security protocols are used to authenticate more transactions, they end up being relied on in legal proceedings. Designers often fail to anticipate this. Here we show how the EMV protocol – the dominant card payment system worldwide – does not produce adequate evidence for resolving disputes. We propose five principles for designing systems to produce robust evidence. We apply these principles to other systems such as Bitcoin, electronic banking and phone payment apps. We finally propose specific modifications to EMV that could allow disputes to be resolved more efficiently and fairly

Forensic Analysis of Smartphone Applications for Privacy Leakage

Smartphone and tablets are personal devices that have diffused to near universal ubiquity in recent years. As Smartphone users become more privacy-aware and -conscious, research is needed to understand how “leakage” of private information (personally identifiable information – PII) occurs. This study explores how leakage studies in Droid devices should be adapted to Apple iOS devices. The OWASP Zed Attack Proxy (ZAP) is examined for 50 apps in various categories. This study confirms that: (1) most apps transmit unencrypted sensitive PII, (2) SSL is used by some recipient websites, but without corresponding app compliance with SSL, and (3) most apps in iOS environments reveal (leak) smartphone version. The paper concludes that much additional work is needed to assess the privacy dominance between platforms and to raise user awareness of smartphone privacy intrusions. Keywords: mobile forensics, ZAP, privacy leakage, metadata, securit

Convicted by memory: Automatically recovering spatial-temporal evidence from memory images

Memory forensics can reveal “up to the minute” evidence of a device’s usage, often without requiring a suspect’s password to unlock the device, and it is oblivious to any persistent storage encryption schemes, e.g., whole disk encryption. Prior to my work, researchers and investigators alike considered data-structure recovery the ultimate goal of memory image forensics. This, however, was far from sufficient, as investigators were still largely unable to understand the content of the recovered evidence, and hence efficiently locating and accurately analyzing such evidence locked in memory images remained an open research challenge. In this dissertation, I propose breaking from traditional data-recovery-oriented forensics, and instead I present a memory forensics framework which leverages program analysis to automatically recover spatial-temporal evidence from memory images by understanding the programs that generated it. This framework consists of four techniques, each of which builds upon the discoveries of the previous, that represent this new paradigm of program-analysis-driven memory forensics. First, I present DSCRETE, a technique which reuses a program’s own interpretation and rendering logic to recover and present in-memory data structure contents. Following that, VCR developed vendor-generic data structure identification for the recovery of in-memory photographic evidence produced by an Android device’s cameras. GUITAR then realized an app-independent technique which automatically reassembles and redraws an app’s GUI from the multitude of GUI data elements found in a smartphone’s memory image. Finally, different from any traditional memory forensics technique, RetroScope introduced the vision of spatial-temporal memory forensics by retargeting an Android app’s execution to recover sequences of previous GUI screens, in their original temporal order, from a memory image. This framework, and the new program analysis techniques which enable it, have introduced encryption-oblivious forensics capabilities far exceeding traditional data-structure recovery

Precognition: Automated Digital Forensic Readiness System for Mobile Computing Devices in Enterprises

Enterprises are facing an unprecedented risk of security incidents due to the influx of emerging technologies, like smartphones and wearables. Most of the current Mobile security systems are not maturing in pace with technological advances. They lack the ability to learn and adapt from the past knowledge base. In the case of a security incident, enterprises find themselves underprepared for the lack of evidence and data. The systems are not designed to be forensic ready. There is a need for automated security analysis and forensically ready solution, which can learn and continuously adapt to new challenges, improve efficiency and productivity of the system. In this research, the authors have designed a security analysis and digital forensic readiness system targeted at smartphones and wearables in an enterprise environment. The proposed system detects applications violating security policies, analyzes Android and iOS applications to identify possible vulnerabilities on the server, apply machine learning algorithms to improve the efficiency and accuracy of vulnerability prediction. The System continuously learns from past incidents, proactively collect required information from the devices which can help in digital forensics. Machine learning techniques are applied to the set of features extracted from the decompiled Mobile applications and applications classified based on consisting of one or more vulnerabilities. The system was evaluated in a real-world enterprise environment with 14151 mobile applications and vulnerabilities was predicted with an accuracy of 94.2%. The system can also work on virtual instances of the mobile devices